PySpark Recipes

A Problem-Solution Approach with PySpark2

Nonfiction, Computers, Database Management, General Computing, Programming
Cover of the book PySpark Recipes by Raju Kumar Mishra, Apress
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Author: Raju Kumar Mishra ISBN: 9781484231418
Publisher: Apress Publication: December 9, 2017
Imprint: Apress Language: English
Author: Raju Kumar Mishra
ISBN: 9781484231418
Publisher: Apress
Publication: December 9, 2017
Imprint: Apress
Language: English

Quickly find solutions to common programming problems encountered while processing big data. Content is presented in the popular problem-solution format. Look up the programming problem that you want to solve. Read the solution. Apply the solution directly in your own code. Problem solved!

PySpark Recipes covers Hadoop and its shortcomings. The architecture of Spark, PySpark, and RDD are presented. You will learn to apply RDD to solve day-to-day big data problems. Python and NumPy are included and make it easy for new learners of PySpark to understand and adopt the model.

**What You Will Learn  **

  • Understand the advanced features of PySpark2 and SparkSQL

  • Optimize your code

  • Program SparkSQL with Python

  • Use Spark Streaming and Spark MLlib with Python

  • Perform graph analysis with GraphFrames

Who This Book Is For

Data analysts, Python programmers, big data enthusiasts

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Quickly find solutions to common programming problems encountered while processing big data. Content is presented in the popular problem-solution format. Look up the programming problem that you want to solve. Read the solution. Apply the solution directly in your own code. Problem solved!

PySpark Recipes covers Hadoop and its shortcomings. The architecture of Spark, PySpark, and RDD are presented. You will learn to apply RDD to solve day-to-day big data problems. Python and NumPy are included and make it easy for new learners of PySpark to understand and adopt the model.

**What You Will Learn  **

Who This Book Is For

Data analysts, Python programmers, big data enthusiasts

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